Computational Terminology covers an increasingly important aspect in
Natural Language Processing areas such as text mining, information
retrieval, information extraction, summarisation, textual entailment,
document management systems, question-answering systems, ontology
building, etc. Terminological information is paramount for knowledge
mining from texts for scientific discovery and competitive
intelligence. Scientific needs in fast growing domains (such as
biomedicine, chemistry and ecology) and the overwhelming amount of
textual data published daily demand that terminology is acquired and
managed systematically and automatically; while in well established
domains (such as law, economy, banking and music) the demand is on
fine-grained analyses of documents for knowledge description and
acquisition. Moreover, capturing new concepts leads to the acquisition
and management of new knowledge.

The aim of this fourth CompuTerm workshop is to bring together Natural
Language Processing researchers to discuss recent advances in
computational terminology and its impact in many NLP applications. The
topics addressed in this workshop are wide ranging:

- term extraction, recognition and filtering, which is the core
of the terminological activity that lays basis for other
terminological topics and tasks;

- event recognition and extraction, that extends the notion of the
terminological entity from terms meaning static units up to terms
meaning procedural and dynamic processes;

- acquisition of semantic relations among terms, which is also an
important research topic as the acquisition of semantic
relationships between terms finds applications such as the
population and update of existing knowledge bases, definition
of domain specific templates in information extraction and
disambiguation of terms;

- term variation management, that helps to deal with the dynamic
nature of terms, their acquisition from heterogeneous sources, their
integration, standardisation and representation for a large range of
applications and resources, is also increasingly important, as one
has to address this research problem when working with various
controlled vocabularies, thesauri, ontologies and textual data. Term
variation is also related to their paraphrases and reformulations,
due to historical, regional, local or personal issues. Besides, the
discovery of synonym terms or term clusters is equally
beneficial to many NLP applications;

- definition acquisition, that covers important research and
aims to provide precise and nonambiguous description of
terminological entities. Such definitions may contain
elements necessary for the formal description of terms and concepts
within ontologies;

- consideration of the user expertise, that is becoming a new issue in
the terminological activity, takes into account the fact that
specialized domains contain notions and terms often
nonunderstandable to non-experts or to laymen (such as patients
within the medical area, or bank clients within banking and economy
areas). This aspect, although related to specialized areas, provides
direct link between specialized languages and general language;

- systematic terminology management and updating domain specific
dictionaries and thesauri, that are important aspects for
maintaining the existing terminological resources. These aspects
become crucial because the amount of the existing terminological
resources is constantly increasing and because their perennial and
efficient use depends on their maintenance and updating, while
their re-acquisition is costly and often non-reproducible;

- monolingual and multilingual resources, that open the possibility
for developing cross-lingual and multi-lingual applications,
requires specific corpora, methods and tools which design and
evaluation are challenging issues;

- robustness and portability of methods, which allows to apply methods
developed in one given context to other contexts (corpora, domains,
languages, etc.) and to share the research expertise among them;

- social netwoks and modern media processing, that attracts an
increasing number of researchers and that provides challenging
material to be processed;

- utilization of terminologies in various NLP applications, as they
are a necessary component of any NLP system dealing with
domain-specific literature, is another novel and challenging
research direction.

The workshop submissions are open to different approaches, ranging
from term extraction in various languages (using verb co-occurrence,
information theoretic approaches, machine learning, etc.), translation
pairs extracting from bilingual corpora based on terminology, up to
semantic oriented approaches and theoretical aspects of terminology.
Besides, experiments on the evaluation of terminological methods and
tools are also encouraged since they provide interesting and useful
proof about the utility of terminological resources:

- direct evaluation may concern the efficiency of the
terminological methods and tools to capture the terminological
entities and relations, as well as various kinds of related
information;

- indirect evaluation may concern the use of terminological resources
in various NLP applications and the impact these resources have on
the performance of the automatic systems. In this case, research and
competition tracks (such as TREC, BioCreative, CLEF, CLEF-eHealth,
I2B2, *SEM, and other shared tasks), provide particularly fruitful
evaluation contexts and proved very successful in identifying key
problems in terminology such as term variation and ambiguity.

We encourage authors to submit their research work related to various
aspects of computational terminology, such as mentioned in this
call. The workshop authors will be proposed to submit an extented
version of their work to a special issue of an international journal
or of a book collection.